The Information Intervention Chain: Interface Layer Example

A couple days ago I wrote up my description of the Information Intervention Chain. One of the points there was that work on each layer decreases the load on the layers below, and helps cover some of the errors not caught in the layers above.

Here’s a simple example, where a user has has responded to someone talking about ivermectin. Their impression — if we take this user at their word, and in this case I do — is that the NIH has started recommending ivermectin.

Now this is false, and I suppose some might say to just ban such things altogether. The NIH is not recommending the use of ivermectin for COVID-19. This is a fact. But I doubt we want to be in the business of policing every small, non-viral, good faith but confused reply people make on social media. Moderation is important, but it needs to be well targeted.

So next we get to the layer of interface. And here we find something pretty interesting. The user believes at least two wrong things:

  1. That this is a recent (late summer/fall) article on the use of ivermectin which negates previous guidance
  2. That this article represents a statement by the NIH

Take a moment to look at the post. Where would they get such ideas?

The fact is that their assumptions are quite reasonable given the failures of the interface to provide context. The article linked here is not from the NIH but rather from the American Journal of Therapeutics. It looks like it comes from the NIH, and that’s largely because the Twitter card (as well as the Facebook card, etc) highlights the address as the source, a side effect of the article being available through a database that is run through the NIH. The card, in this case, actively creates the wrong impression.

The second point — is it new? Note that when the link is shared there is no indication of the publication date of the article. So this article was actually published in the spring, and is, at best, out of date at this point. But Twitter chooses to not make the date of the article visible in the shared card. And that’s not a dig on just Twitter here — at least as far as I can tell, the PubMed page doesn’t expose the publication date or the journal name at the meta level. Somewhat shockingly there seems to be no Facebook or Twitter-specific meta info at all. Even if Twitter wanted to make publication and publication date more visible, it’s not clear the site gives them the information they would need to do it.

Now once you click through, you should be good. Should be good, but I’ll get to that in a moment.

Here’s the good news, if you click the link to the page, you see some of the information of which this person was unaware: the journal name, the fact that it’s on PubMed, the date at the top. But even here we are undone by confusing interface choices.

That banner at the top? From the NIH, supposedly? What does it say?

It says that this is the Library of Medicine by the National Institutes of Health, and you’re in luck, because there’s some important COVID-19 guidance below!

Wait, that’s not what a big banner with an exclamation point saying “COVID-19 Information” means? So tell me what an average person is supposed to think an exclamation-marked heading on an NIH site saying “COVID-19 Information” indicates?

It’s supposed to mean that what is below it is not official?

Well, good luck with that.

People keep wanting to talk about how people are hopelessly biased, or cynical, or post-truth, or whatever. And sure, maybe. But how would we know? How would we possibly know when someone engaging in a plain text reading of both what Twitter and the NIH is providing them here would come to this exact conclusion, that the NIH is now recommending they take ivermectin?

Now, can the layer below the interface intervention — in this case, the individual layer of educational interventions — clean this up? Well, educators have been trying to. Understanding things like the difference between an aggregation site like PubMed and a publisher like the American Journal of Therapeutics are things we teach students. But coming back to the “load” metaphor, it would make a lot more sense to clean this mess up at the interface layer, at least for a major site like PubMed. I mean, I can try to teach several billion people what PubMed is, or, alternatively, Twitter, Facebook, and PubMed itself could choose to make it clear what PubMed is at the interface layer, which would allow education to focus limited time on more difficult problems.

Nothing — not in any of the layers — is determinative in itself. But improving the information environment means chipping away at the things that can be done, in each of the layers, until the problems left are truly only the hard ones. We still aren’t anywhere near to that point.